Applied AI Scientist, Language + Context
Echo Neurotechnologies
Salary undisclosed
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Description
Company Overview
Echo Neurotechnologies is an exciting new startup in the Brain-Computer Interface (BCI) space, driving innovation through advanced hardware engineering and AI solutions. Our mission is to deliver cutting-edge technologies that restore autonomy to people living with disabilities and improve their quality of life.
Team Culture
Join a small, dedicated team of knowledgeable and motivated professionals. Our early-stage environment offers the opportunity to take ownership of broad decisions with significant and long-lasting impact. We emphasize continuous learning and growth, fostering cross-functional collaboration where your contributions are vital to our success.
SUMMARY
We are seeking an experienced Applied AI Scientist, with a focus on language & context modeling, to join our team. The person who fills this role will apply ML/AI principles and practices to designing, developing, fine-tuning, personalizing, and miniaturizing flexible language and context models for use within brain-computer interface applications to have real-world impact on patients with physical disabilities.
PRIMARY ROLE AND RESPONSIBILITIES
- Language modeling
- Leverage a deep understanding of LMs to create custom solutions for brain-computer interface applications, including LLM fine-tuning, customization, and dissection
- Explore a variety of LM strategies of various scales and complexities for tailored integration into other decoding pipelines
- Characterize agentic AI tools for suitability in product user interfaces
- Context modeling
- Design and build ML pipelines capable of performing flexible, real-time inference with multiple input streams
- Deploy custom or off-the-shelf state-of-the-art models for parsing audio, video, and application states
- Perform context engineering to aggregate and model contextual information for use in downstream decoders
- General ML practices & company standards
- Model dissection and interpretability to extract information-rich latent representations from large models (e.g. pretrained foundation models) for broad and generalized use in other models
- Model miniaturization for low-latency and computationally inexpensive processing
- Work collaboratively and effectively within a small, cross-functional team to hit both R&D and product-focused goals
- Maintain versioned, clear, and highly documented code, analysis pipelines, and results for maximum interpretability and reproducibility
- Contribute to documentation for a Quality Management System, as appropriate and relevant to ML implementations that become part of medical products
QUALIFICATIONS
- Bachelor's or Master's degree in Math, Engineering, Data Science, or other relevant quantitative field
- A minimum of 5 years of combined academic and professional ML experience
- Experience deploying ML models in an industry setting
- Experience designing, developing, and deploying LM models in an industry setting
- Experience designing, training, and evaluating transformers
- Proficiency in Python and PyTorch
- Proficiency in using GPUs and GPU software toolkits to accelerate ML pipelines
OTHER QUALIFICATIONS
- Experience working with reinforcement learning, LLM alignment and safety, and multilingual modeling
- Experience developing foundation models and applying transfer-learning techniques
- Experience working with high-dimensional time-series datasets
- Experience working on medical or clinical applications
- Experience translating methods described in scientific publications to available datasets
- Experience working with speech-recognition, video-processing, and application-parsing models
What We Offer
An opportunity to work on exciting, cutting-edge projects to transform patients’ lives in a highly collaborative work environment.
Competitive compensation, including stock options.
Comprehensive benefits package.
401(k) program with matching contributions.
Equal Opportunity Employer
Echo Neurotechnologies is an Equal Opportunity Employer (EOE). We celebrate diversity and are committed to creating an inclusive environment for all employees.
Confidentiality
All applications will be treated confidentially. Applicants may be asked to sign an NDA after the initial stages of the interview process.
Benefits
- An opportunity to work on exciting, cutting-edge projects to transform patients’ lives in a highly collaborative work environment.
- Competitive compensation, including stock options.
- Comprehensive benefits package.
- 401(k) program with matching contributions.
About this role
Echo Neurotechnologies is building brain-computer interfaces to restore autonomy for people with physical disabilities, and they're looking for an Applied AI Scientist to develop the language and context modeling that powers these systems. You'd own the full pipeline: fine-tuning and customizing language models for BCI applications, building real-time inference systems that parse audio, video, and application state, and miniaturizing models for low-latency deployment. This means working across model dissection, interpretability, and practical optimization—taking research-grade approaches and making them work in a medical product context.
The role demands at least five years of ML experience with proven track record deploying models in industry, plus specific expertise in language models, transformers, and PyTorch. You should be comfortable moving between research and engineering: understanding how to extract useful representations from foundation models while also shipping code that's documented, versioned, and ready for a Quality Management System. Experience with reinforcement learning, LLM safety, time-series data, or medical applications would strengthen your candidacy, though the core requirement is solid applied ML fundamentals and hands-on language model work.
This is an in-office role in San Francisco at an early-stage startup, which means your work will have direct visibility and impact on product decisions. You'd be joining a small, cross-functional team where ownership and continuous learning are expected—not a large research organization, but a place where your contributions shape the direction of the technology.
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